TCIU (version 1.2.7)

fmri_post_hoc: post-hoc process for p values

Description

This function is used to conduct the post-hoc process (i.e. FDR correction and spatial clustering) for a 3-dimensional p-value array.

Usage

fmri_post_hoc(
  p_val_3d,
  fdr_corr = NULL,
  spatial_cluster.thr = NULL,
  spatial_cluster.size = NULL,
  show_comparison = FALSE,
  ...
)

Value

3D p-values after FDR correction or spatial clustering

Arguments

p_val_3d

an array which contains the p-values as the result of fMRI statistical tests.

fdr_corr

The default is NULL. Input 'fdr' to conduct FDR correction.

spatial_cluster.thr

The default is NULL. Together with spatial_cluster.size are used to filter contiguous clusters of locations in a 3D array that are below some threshold and with some minimum size.

spatial_cluster.size

The default is NULL. The size of spatial cluster.

show_comparison

The default is FALSE. If TRUE, the output would display the comparison between raw and processed p-values.

...

One can specify breaks etc. to modify the comparison histogram in ggplot2.

Author

SOCR team <http://socr.umich.edu/people/>

Details

The function fmri_post_hoc would help do the FDR correction and spatial clustering for a 3d p-value array. The FDR correction controls for a low proportion of false positives, while the spatial clustering part help filter out all sparse p-values that are not in specified clusters.

Examples

# sample 3D p value provided by the package
dim(phase2_pval)
# \donttest{
# do the FDR correction
pval_fdr = fmri_post_hoc(phase2_pval, 
                         fdr_corr = 'fdr',
                         spatial_cluster.thr = NULL,
                         spatial_cluster.size = NULL, 
                         show_comparison = FALSE)

# do the spatial clustering
pval_posthoc = fmri_post_hoc(pval_fdr,
                             fdr_corr = NULL,
                             spatial_cluster.thr = 0.05,
                             spatial_cluster.size = 5, 
                             show_comparison = FALSE)
# }